As the population becomes increasingly dependent on computing resources, the need for more computers and access to them becomes larger and more important. Today, millions of people use computing devices with an ever increasing need to have access to them. As a consequence, computing administrators need to be able to accommodate this need and be able to adapt to the volume of software instructions given to computing devices by the many users as well as the numerous applications that run on them. However, a problem remains as to how to adequately forecast computing resources in a dynamic environment. For example, a typical computer may need to handle millions of instructions from a few applications but also may need to handle a group of new users. A challenge is to be able to forecast when a computer or set of computers has reached its capacity in executing both instruction sets from the various applications running on it as well as its ability to handle an increasing number of users wanting access to computing resources. The performance of an entire network can progressively degrade as one or more computers approach their capacity. There is a pervasive need to control the number of computers operating in a network, operating as servers, or operating as other computing devices, and to be able to forecast when such computers need their resources increased or augmented.
Users and application executions are increasing at an alarming rate placing enormous burdens on system resources. A challenge has become a battle to keep pace with these demands by checking and maintaining computers very often to ensure that they can handle the capacity needs placed upon them by the ever increasing number of users and demand for executing more applications.